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Nomogram Model for Predicting Cause-Specific Mortality in Patients with Stage I Small-Cell Lung Cancer: A Competing Risk Analysis
ziping wang
Beijing Cancer Hospital
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Cancer.
Background: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer(SCLC) who were instructed to undergo surgery was from 40% to 60%.The death competition influence the accuracy of the classical survival analyses.The aim of the study is to investigate the mortality of stage I small-cell lung cancer (SCLC) patients in the presence of competing risks according to a proportional hazards model, and to establish a competing risk nomogram to predict probabilities of both cause-specific death and death resulting from other causes.
Methods : The study subjects were patients diagnosed with stage I SCLC according to ICD-O-3. First, the cumulative incidence functions (CIFs) of cause-specific death, as well as of death resulting from other causes, were calculated. Then, a proportional hazards model for the sub-distribution of competing risks and a monogram were constructed to evaluate the probability of mortality in stage I SCLC patients.
Results: 1811 patients were included in this study. The five-year probabilities of death due to specific causes and other causes were 61.5% and 13.6%, respectively. Tumor size, extent of tumor, surgery, and radiotherapy were identified as the predictors of death resulting from specific causes in stage I SCLC. The results showed that surgery could effectively reduce the cancer-specific death, and the one-year cumulative incidence dropped from 34.5% to 11.2%. Like surgery, chemotherapy and radiotherapy improved the one-year survival rate.
Conclusions: We constructed a predictive model for stage I SCLC using the data from the SEER database. The proportional sub-distribution models of competing risks revealed the predictors of death resulting from both specific causes and other causes. The competing risk nomogram that we built to predict the prognosis showed good reliability and could provide beneficial and individualized predictive information for stage I SCLC patients.
Keywords
SCLC, Competing risks, Cumulative incidence, Nomogram
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CURRENT STATUS: Published
Version 5
Posted 14 Aug, 2020
Published
On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 30 Jul, 2020
Editor assigned
On 29 Jul, 2020
Submission checks complete
On 28 Jul, 2020
Editor invited
On 28 Jul, 2020
No comments provided
Editorial decision: Major revision
On 17 Jul, 2020
Review #1 received
Received 09 Jul, 2020
Reviewers invited
Invitations sent on 02 Jul, 2020
Reviewer #1 agreed
On 02 Jul, 2020
Editor assigned
On 29 Jun, 2020
Submission checks complete
On 28 Jun, 2020
Editor invited
On 28 Jun, 2020
No comments provided
Editorial decision: Major revision
On 12 Jun, 2020
Review #2 received
Received 14 Apr, 2020
Review #1 received
Received 14 Apr, 2020
Reviewer #2 agreed
On 13 Apr, 2020
Reviewer #1 agreed
On 21 Mar, 2020
Reviewers invited
Invitations sent on 16 Mar, 2020
Editor assigned
On 27 Feb, 2020
Submission checks complete
On 26 Feb, 2020
Editor invited
On 26 Feb, 2020
No comments provided
Editorial decision: Minor revision
On 21 Feb, 2020
Reviewers invited
Invitations sent on 07 Jan, 2020
Reviewer #1 agreed
On 07 Jan, 2020
Review #1 received
Received 07 Jan, 2020
Editor assigned
On 03 Jan, 2020
Submission checks complete
On 02 Jan, 2020
Editor invited
On 02 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 23 Dec, 2019
Review #1 received
Received 19 Nov, 2019
Reviewer #1 agreed
On 07 Nov, 2019
Reviewers invited
Invitations sent on 04 Nov, 2019
Submission checks complete
On 29 Sep, 2019
Editor invited
On 23 Sep, 2019
Editor assigned
On 23 Sep, 2019
First submitted
On 19 Sep, 2019
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This preprint is under consideration at BMC Cancer. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Nomogram Model for Predicting Cause-Specific Mortality in Patients with Stage I Small-Cell Lung Cancer: A Competing Risk Analysis
ziping wang
Beijing Cancer Hospital
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 5
Posted 14 Aug, 2020
Published
On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 30 Jul, 2020
Editor assigned
On 29 Jul, 2020
Submission checks complete
On 28 Jul, 2020
Editor invited
On 28 Jul, 2020
No comments provided
Editorial decision: Major revision
On 17 Jul, 2020
Review #1 received
Received 09 Jul, 2020
Reviewers invited
Invitations sent on 02 Jul, 2020
Reviewer #1 agreed
On 02 Jul, 2020
Editor assigned
On 29 Jun, 2020
Submission checks complete
On 28 Jun, 2020
Editor invited
On 28 Jun, 2020
No comments provided
Editorial decision: Major revision
On 12 Jun, 2020
Review #2 received
Received 14 Apr, 2020
Review #1 received
Received 14 Apr, 2020
Reviewer #2 agreed
On 13 Apr, 2020
Reviewer #1 agreed
On 21 Mar, 2020
Reviewers invited
Invitations sent on 16 Mar, 2020
Editor assigned
On 27 Feb, 2020
Submission checks complete
On 26 Feb, 2020
Editor invited
On 26 Feb, 2020
No comments provided
Editorial decision: Minor revision
On 21 Feb, 2020
Reviewers invited
Invitations sent on 07 Jan, 2020
Reviewer #1 agreed
On 07 Jan, 2020
Review #1 received
Received 07 Jan, 2020
Editor assigned
On 03 Jan, 2020
Submission checks complete
On 02 Jan, 2020
Editor invited
On 02 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 23 Dec, 2019
Review #1 received
Received 19 Nov, 2019
Reviewer #1 agreed
On 07 Nov, 2019
Reviewers invited
Invitations sent on 04 Nov, 2019
Submission checks complete
On 29 Sep, 2019
Editor invited
On 23 Sep, 2019
Editor assigned
On 23 Sep, 2019
First submitted
On 19 Sep, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Cancer.
Background: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer(SCLC) who were instructed to undergo surgery was from 40% to 60%.The death competition influence the accuracy of the classical survival analyses.The aim of the study is to investigate the mortality of stage I small-cell lung cancer (SCLC) patients in the presence of competing risks according to a proportional hazards model, and to establish a competing risk nomogram to predict probabilities of both cause-specific death and death resulting from other causes.
Methods : The study subjects were patients diagnosed with stage I SCLC according to ICD-O-3. First, the cumulative incidence functions (CIFs) of cause-specific death, as well as of death resulting from other causes, were calculated. Then, a proportional hazards model for the sub-distribution of competing risks and a monogram were constructed to evaluate the probability of mortality in stage I SCLC patients.
Results: 1811 patients were included in this study. The five-year probabilities of death due to specific causes and other causes were 61.5% and 13.6%, respectively. Tumor size, extent of tumor, surgery, and radiotherapy were identified as the predictors of death resulting from specific causes in stage I SCLC. The results showed that surgery could effectively reduce the cancer-specific death, and the one-year cumulative incidence dropped from 34.5% to 11.2%. Like surgery, chemotherapy and radiotherapy improved the one-year survival rate.
Conclusions: We constructed a predictive model for stage I SCLC using the data from the SEER database. The proportional sub-distribution models of competing risks revealed the predictors of death resulting from both specific causes and other causes. The competing risk nomogram that we built to predict the prognosis showed good reliability and could provide beneficial and individualized predictive information for stage I SCLC patients.
Figure 1
Figure 2
Figure 3
Figure 4